25

是否可以将多个窗口功能应用于同一个分区？（如果我没有使用正确的词汇，请纠正我）

例如你可以做

SELECT name, first_value() over (partition by name order by date) from table1

但是有没有办法做类似的事情：

SELECT name, (first_value() as f, last_value() as l (partition by name order by date)) from table1

我们在哪里将两个函数应用到同一个窗口？

参考： http: //postgresql.ro/docs/8.4/static/tutorial-window.html

4

2 回答 2

32

你能不能只使用每个选择的窗口

就像是

SELECT  name, 
        first_value() OVER (partition by name order by date) as f, 
        last_value() OVER (partition by name order by date) as l 
from table1

同样从您的参考资料中，您可以这样做

SELECT sum(salary) OVER w, avg(salary) OVER w
FROM empsalary
WINDOW w AS (PARTITION BY depname ORDER BY salary DESC)
于 2009-12-13T10:29:01.733 回答
18

警告：我不会删除此答案，因为它在技术上似乎是正确的，因此可能会有所帮助，但请注意这可能PARTITION BY bar ORDER BY foo不是您想要做的。实际上，聚合函数不会将分区元素作为一个整体进行计算。也就是说，SELECT avg(foo) OVER (PARTITION BY bar ORDER BY foo) 不等于（SELECT avg(foo) OVER (PARTITION BY bar)见答案末尾的证明）。

虽然它本身并没有提高性能，但如果您多次使用同一个分区，您可能希望使用 asstander 提出的第二种语法，这不仅是因为它更便宜。这就是为什么。

考虑以下查询：

SELECT 
  array_agg(foo)
    OVER (PARTITION BY bar ORDER BY foo), 
  avg(baz)
    OVER (PARTITION BY bar ORDER BY foo) 
FROM 
  foobar;

由于原则上排序对平均值的计算没有影响，您可能会想改用以下查询（在第二个分区上没有排序）：

SELECT 
  array_agg(foo) 
    OVER (PARTITION BY bar ORDER BY foo), 
  avg(baz)
    OVER (PARTITION BY bar) 
FROM 
  foobar;

这是一个很大的错误，因为它需要更长的时间。证明 ：

> EXPLAIN ANALYZE SELECT array_agg(foo) OVER (PARTITION BY bar ORDER BY foo), avg(baz) OVER (PARTITION BY bar ORDER BY foo) FROM foobar;
                                                           QUERY PLAN                                                        
---------------------------------------------------------------------------------------------------------------------------------
 WindowAgg  (cost=215781.92..254591.76 rows=1724882 width=12) (actual time=969.659..2353.865 rows=1724882 loops=1)
   ->  Sort  (cost=215781.92..220094.12 rows=1724882 width=12) (actual time=969.640..1083.039 rows=1724882 loops=1)
         Sort Key: bar, foo
         Sort Method: quicksort  Memory: 130006kB
         ->  Seq Scan on foobar  (cost=0.00..37100.82 rows=1724882 width=12) (actual time=0.027..393.815 rows=1724882 loops=1)
 Total runtime: 2458.969 ms
(6 lignes)

> EXPLAIN ANALYZE SELECT array_agg(foo) OVER (PARTITION BY bar ORDER BY foo), avg(baz) OVER (PARTITION BY bar) FROM foobar;
                                                              QUERY PLAN                                                           
---------------------------------------------------------------------------------------------------------------------------------------
 WindowAgg  (cost=215781.92..276152.79 rows=1724882 width=12) (actual time=938.733..2958.811 rows=1724882 loops=1)
   ->  WindowAgg  (cost=215781.92..250279.56 rows=1724882 width=12) (actual time=938.699..2033.172 rows=1724882 loops=1)
         ->  Sort  (cost=215781.92..220094.12 rows=1724882 width=12) (actual time=938.683..1062.568 rows=1724882 loops=1)
               Sort Key: bar, foo
               Sort Method: quicksort  Memory: 130006kB
               ->  Seq Scan on foobar  (cost=0.00..37100.82 rows=1724882 width=12) (actual time=0.028..377.299 rows=1724882 loops=1)
 Total runtime: 3060.041 ms
(7 lignes)

现在，如果您知道这个问题，当然您将在任何地方使用相同的分区。但是当你有十次或更多相同的分区并且你在几天内更新它时，很容易忘记在ORDER BY不需要它的分区上添加子句。

语法来了WINDOW，它可以防止你犯这种粗心的错误（当然，前提是你知道最好尽量减少不同窗口函数的数量）。EXPLAIN ANALYZE以下内容与第一个查询严格等效（据我所知）：

SELECT
  array_agg(foo)
    OVER qux,
  avg(baz)
    OVER qux
FROM
  foobar
WINDOW
  qux AS (PARTITION BY bar ORDER BY bar)

预警更新：

我理解“SELECT avg(foo) OVER (PARTITION BY bar ORDER BY foo) 不等于”的说法SELECT avg(foo) OVER (PARTITION BY bar)似乎有问题，所以这里有一个例子：

# SELECT * FROM foobar;
 foo | bar 
-----+-----
   1 |   1
   2 |   2
   3 |   1
   4 |   2
(4 lines)

# SELECT array_agg(foo) OVER qux, avg(foo) OVER qux FROM foobar WINDOW qux AS (PARTITION BY bar);
 array_agg | avg 
-----------+-----
 {1,3}     |   2
 {1,3}     |   2
 {2,4}     |   3
 {2,4}     |   3
 (4 lines)

# SELECT array_agg(foo) OVER qux, avg(foo) OVER qux FROM foobar WINDOW qux AS (PARTITION BY bar ORDER BY foo);
 array_agg | avg 
-----------+-----
 {1}       |   1
 {1,3}     |   2
 {2}       |   2
 {2,4}     |   3
(4 lines)
于 2014-10-01T12:13:23.640 回答